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\n ESFA Logo\n

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\n \n OFFICIAL SENSITIVE\n \n

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\n Interactive Analysis Template\n \n \xc2\xb6\n \n

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\n Contents\n \n \xc2\xb6\n \n

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\n Summary\n \n \xc2\xb6\n \n

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\n This template demonstrates how to develop and share interactive reproducible analysis using Python and Jupyter Lab.\n

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\n The data used in this template is for learning purposes only.\n

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\n Packages\n \n \xc2\xb6\n \n

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\n Data import\n \n \n \n \xc2\xb6\n \n

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\n The data sources used are fictional exam scores from Kaggle and a dataset from ONS on 18-24 student population over time. The datasets can be found at\n \n https://www.kaggle.com/spscientist/students-performance-in-exams\n \n and\n \n https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/livebirths/articles/howhasthestudentpopulationchanged/2016-09-20\n \n

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\n The exam performance data comprises 5,000 records (rows) and 8 features (columns).\n

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\n Data processing\n \n \n \n \xc2\xb6\n \n

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\n Transform the 18 to 24 student population from string 1,000 format to decimal 1000.00 using ASCII to float (atof).\n

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\n Add year and month columns to 18-24 student population data.\n

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\n Summary statistics\n \n \xc2\xb6\n \n

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\n Interactive analysis\n \n \xc2\xb6\n \n

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\n 18-24 student population doubled since 1992\n \n \xc2\xb6\n \n

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\n Student numbers (aged 18-24) have almost doubled since 1992. In 2016, the student population was around 1,896,000\n

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\n Recommendations\n \n \n \n \xc2\xb6\n \n

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\n References\n \n \n \n \xc2\xb6\n \n

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